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Academic literature on the topic 'Vibration filtering'
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Journal articles on the topic "Vibration filtering"
1
Feltane, S., S. Yahyaoui, A. Hafsaoui, and A. Boussaid. "Signal processing application for vibration generated by blasting in tunnels." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 5 (2020): 54–60. http://dx.doi.org/10.33271/nvngu/2021-5/054.
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Purpose. To study the vibrations waves generated by blasting in a tunnel using the signal processing tools. Methodology. Field tests are carried out to measure vibration wave during blasting operations at different locations in the tunnel and its immediate environment. Results of the measurements are processed by the autocorrelation method, which consists of filtering based on signal shape recognition. A comparison is accomplished between the peak particle velocities (PPV) measured and those obtained after filtering. Findings. The results obtained after filtering gave a significant reduction in PPV of the measured vibration amplitudes in comparison to those obtained after treatment for the three components: longitudinal, transversal and vertical ones. Good knowledge of vibration source is important for amplitude attenuation regarding the observed difference between the recorded seismogram during explosion of a single unit charge and other standard explosions. Originality. The work introduces signal processing methods for filtering vibration signals related to blasting, which is insufficiently studied. Practical value. This study shows that the treatment of blasting vibrations by a filtering method should reduce the peak velocity of the particles by separating the signals and eliminating the interference in the initial signal.
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Mortimer, B. "A Spider’s Vibration Landscape: Adaptations to Promote Vibrational Information Transfer in Orb Webs." Integrative and Comparative Biology 59, no. 6 (2019): 1636–45. http://dx.doi.org/10.1093/icb/icz043.
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Abstract Spider orb webs are used not only for catching prey, but also for transmitting vibrational information to the spider. Vibrational information propagates from biological sources, such as potential prey or mates, but also abiotic sources, such as wind. Like other animals, the spider must cope with physical constraints acting on the propagation of vibrational information along surfaces and through materials—including loss of energy, distortion, and filtering. The spider mitigates these physical constraints by making its orb web from up to five different types of silks, closely controlling silk use and properties during web building. In particular, control of web geometry, silk tension, and silk stiffness allows spiders to adjust how vibrations spread throughout the web, as well as their amplitude and speed of propagation, which directly influences energy loss, distortion, and filtering. Turning to how spiders use this information, spiders use lyriform organs distributed across their eight legs as vibration sensors. Spiders can adjust coupling to the silk fibers and use posture to modify vibrational information as it moves from the web to the sensors. Spiders do not sense all vibrations equally—they are least sensitive to low frequencies (<30 Hz) and most sensitive to high frequencies (ca. 1 kHz). This sensitivity pattern cannot be explained purely by the frequency range of biological inputs. The role of physical and evolutionary constraints is discussed to explain spider vibration sensitivity and a role of vibration sensors to detect objects on the web as a form of echolocation is also discussed.
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Wu, Junjie, Yufei Sun, Peng Guo, Lihui Feng, Yongbin Zhang, and Youqi Zhang. "Effect of Resonance Interference on MEMS Gyroscopes and Filtering Algorithm Elimination." Journal of Physics: Conference Series 2224, no. 1 (2022): 012128. http://dx.doi.org/10.1088/1742-6596/2224/1/012128.
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Abstract The mechanical structure of MEMS gyroscope is a spring-mass-damper system, which is susceptible to interference near the resonant frequency. This work compared the interference effects of mechanical vibrations and high frequency sound waves on MEMS gyroscopes. Three MEMS gyroscopes ADXRS620 were interfered by vibrations and sound waves near the resonant frequency. The error outputs increased linearly with the increase of interference intensity. The maximum error output could reach 88.95 °/s, which seriously affect the normal operation of the gyroscope. The waveforms of gyroscope outputs under acoustic and vibration interference were almost coincident, which showed the similarity of acoustic and vibration interference. However, to produce the same effect on gyroscopes, the power required of vibration interference was much less than that of acoustic interference. Taking one of the gyroscopes for example, when the SPL of acoustic interference was up to 90 dB, the maximum error was only 3.37 °/s. But when the acceleration amplitude of vibration interference reached 0.050 g, the maximum error was 3.42 °/s. In addition, the effectiveness against vibration interference of the filtering algorithm based on orthogonal demodulation was verified by testing the self-developed gyroscope. Vibration interference could be reduced by 98.88% at most.
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Lin, Yun, Linghan Zhang, Hongwei Han, Yang Li, Wenjie Shen, and Yanping Wang. "Periodic-Filtering Method for Low-SNR Vibration Radar Signal." Remote Sensing 15, no. 14 (2023): 3461. http://dx.doi.org/10.3390/rs15143461.
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Radar is a non-contact, high-precision vibration measurement device and an important tool for bridge vibration monitoring. Vibration information needs to be extracted from the radar phase, but the radar phase information is sensitive to noise. Under low signal-to-noise ratio (SNR) data acquisition conditions, such as low radar transmission power or a long observation distance, differential phase jump errors occur and clutter estimation becomes difficult, which leads to inaccurate inversion of vibration deformation. Traditional low-pass filtering methods can filter out noise to improve SNR, but they require oversampling. The sampling rate needs to be several times higher than the Doppler bandwidth, which is several times higher than the vibration frequency. This puts high data acquisition requirements on radar systems and causes large data volumes. Therefore, this paper proposes a novel vibration signal filtering method called the periodic filtering method. The method uses the periodicity feature of vibration signals for filtering without oversampling. This paper derives the time-domain and frequency-domain expressions for the periodic filter and presents a deformation inversion process based on them. The process involves extracting the vibration frequency in the Doppler domain, suppressing noise through periodic filtering, estimating clutter using circle fitting on the data complex plane, and inverting final deformation with differential phase. The method is verified through simulation experiments, calibration experiments, and bridge vibration experiments. The results show that the new periodic filtering method can improve the SNR by five times, resolve differential phase jumps, and accurately estimate clutter, thus getting submillimeter-level vibration deformation at low SNR.
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Huang, Xili, Cheng Zhang, Hongchen Pang, et al. "Ultra−Wide Range Vibration Frequency Detection Sensors Based on Elastic Steel Triboelectric Nanogenerators for Intelligent Machinery Monitoring." Nanomaterials 12, no. 16 (2022): 2790. http://dx.doi.org/10.3390/nano12162790.
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Vibration measurement and analysis play an important role in diagnosing mechanical faults, but existing vibration sensors are limited by issues such as dependence on external power sources and high costs. To overcome these challenges, the use of triboelectric nanogenerator (TENG)−based vibration sensors has recently attracted attention. These vibration sensors measure a small range of vibration frequencies and are not suitable for measuring high-frequency vibrations. Herein, a self-powered vibration sensor based on an elastic steel triboelectric nanogenerator (ES−TENG) is proposed. By optimizing the elastic steel sheet structure and combining time-frequency transformation and filtering processing methods, the measurement of medium- and high-frequency vibrations is achieved. These results demonstrate that the ES−TENG can perform vibration measurements in the range of 2–10,000 Hz, with a small average error (~0.42%) between the measured frequency and external vibration frequency values. Therefore, the ES−TENG can be used as a self-powered, highly-accurate vibration sensor for intelligent machinery monitoring.
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HISATANI, Masujiro. "Adaptive Filtering for Unbalance Vibration Suppression." Transactions of the Japan Society of Mechanical Engineers Series C 62, no. 597 (1996): 1706–11. http://dx.doi.org/10.1299/kikaic.62.1706.
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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (2021): 144. http://dx.doi.org/10.3390/w13020144.
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Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.
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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (2021): 144. http://dx.doi.org/10.3390/w13020144.
Full textAbstract:
Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.
9
Liu, Ning, and Thomas Schumacher. "Improved Denoising of Structural Vibration Data Employing Bilateral Filtering." Sensors 20, no. 5 (2020): 1423. http://dx.doi.org/10.3390/s20051423.
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With the continuous advancement of data acquisition and signal processing, sensors, and wireless communication, copious research work has been done using vibration response signals for structural damage detection. However, in actual projects, vibration signals are often subject to noise interference during acquisition and transmission, thereby reducing the accuracy of damage identification. In order to effectively remove the noise interference, bilateral filtering, a filtering method commonly used in the field of image processing for improving data signal-to-noise ratio was introduced. Based on the Gaussian filter, the method constructs a bilateral filtering kernel function by multiplying the spatial proximity Gaussian kernel function and the numerical similarity Gaussian kernel function and replaces the current data with the data obtained by weighting the neighborhood data, thereby implementing filtering. By processing the simulated data and experimental data, introducing a time-frequency analysis method and a method for calculating the time-frequency spectrum energy, the denoising abilities of median filtering, wavelet denoising and bilateral filtering were compared. The results show that the bilateral filtering method can better preserve the details of the effective signal while suppressing the noise interference and effectively improve the data quality for structural damage detection. The effectiveness and feasibility of the bilateral filtering method applied to the noise suppression of vibration signals is verified.
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Hornik, Beata, Jan Duława, Czesław Marcisz, Wojciech Korchut, and Jacek Durmała. "The Effect of Mechanically-Generated Vibrations on the Efficacy of Hemodialysis; Assessment of Patients’ Safety: Preliminary Reports." International Journal of Environmental Research and Public Health 16, no. 4 (2019): 594. http://dx.doi.org/10.3390/ijerph16040594.
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Muscle activity during a hemodialysis procedure improves its efficacy. We have formulated a hypothesis that vibrations generated by a specially-designed dialysis chair can, the same as physical exercise, affect the filtering of various fluids between fluid spaces during the hemodialysis procedure. This prospective and interventional study included 21 dialyzed patients. During a single dialysis session, each patient used a prototype device with the working name “vibrating chair”. The chair’s drive used a low-power cage induction motor, which, along with the worm gear motor, was a part of the low-frequency (3.14 Hz) vibration-generating assembly with an amplitude of 4 mm. Tests and measurements were performed before and after the vibration dialysis. After a single hemodialysis session including five 3-min cycles of vibrations, an increase in K t / V in relation to non-vibration K t / V ( 1.53 ± 0.26 vs. 1.62 ± 0.23 ) was seen. Urea reduction ratio increased significantly ( 0.73 ± 0.03 vs. 0.75 ± 0.03 ). A significant increase in systolic blood pressure was observed between the first and the third measurement ( 146 ± 18 vs. 156 ± 24 ). The use of a chair generating low-frequency vibrations increased dialysis adequacy; furthermore, it seems an acceptable and safe alternative to intradialytic exercise.